Radiologists view medical images such as x-rays to determine if a patient has problems or deficiencies that are indicated primarily by such medical images. These images preferably have a high resolution in order for the radiologist to make a diagnosis with some confidence of the existence of a medical problem or deficiency in the patient and, if the medical problem or deficiency exists, a diagnosis of the location and seriousness of such medical problem or deficiency. By way of illustration, each x-ray may indicate the existence of a bone fracture in a patient's body or the existence of a cancer in a patient's lung or in a patient's breast. A high resolution in an x-ray image may constitute 5000 pixels in each horizontal line and 4000 lines vertically. To provide a gray scale of a high resolution for each pixel, each pixel in the image may be defined by as many as 12 binary bits.
With increasing frequency in large institutions such as hospitals, the medical images (e.g. x-rays) for a patient are stored at a central location in the hospitals. The radiologist may be displaced in the hospital from such central location. When the radiologist desires to view these medical images, the images are transmitted from the central location to the radiologist's location. One of the most demanding problems in digital radiology today is the presentation of high resolution medical imagery and digital radiographs to a radiologist for reading. For instance in mammography, a study consists of four (4) extremely high resolution views of the tissue, two (2) from the current session and two (2) from a previous session for comparison purposes. As previously indicated, each view can be as large as 4000 (4k) pixels by 5000 (5k) pixels with each pixel 12 bits in depth. Without compression, a single study would consume more than 160 megabytes of digital storage.
To conserve digital storage media as well as network bandwidth, some form of data compression is needed. However, data compression algorithms generally need a large amount of computational power to shrink an image in compression or to expand an image in decompression. For example, a well written software algorithm can process 2 million to 3 million pixels per second when running on today's high end personal computer. A time period between approximately thirty (30) and forty (40) seconds is required to decompress and display an entire study of four (4) images. This time period is clearly unacceptable to a radiologist.
In addition to software, the industry has also developed several JPEG chips that are targeted at the video authoring market. JPEG is a form of digital compression that constitutes a standard in the industry. These chips operate in real time on video data of medium resolution. When this hardware is used, a radiologist would illustratively be able to view a study in about 5 seconds. This delay is on the border of being acceptable to a radiologist but is not acceptable to the radiologist.